Regulatory and sequence evolution in response to selection for improved associative learning ability in Nasonia vitripennis

Next-generation biological control: the need for integrating genetics and genomics

Biological control is widely successful at controlling pests, but effective biocontrol agents are now more difficult to import from countries of origin due to more restrictive international trade laws (the Nagoya Protocol). Coupled with increasing demand, the efficacy of existing and new biocontrol agents needs to be improved with genetic and genomic approaches. Although they have been underutilised in the past, application of genetic and genomic techniques is becoming more feasible from both technological and economic perspectives. We review current methods and provide a framework for using them. First, it is necessary to identify which biocontrol trait to select and in what direction. Next, the genes or markers linked to these traits need be determined, including how to implement this information into a selective breeding program. Choosing a trait can be assisted by modelling to account for the proper agro-ecological context, and by knowing which traits have sufficiently high heritability values. We provide guidelines for designing genomic strategies in biocontrol programs, which depend on the organism, budget, and desired objective. Genomic approaches start with genome sequencing and assembly. We provide a guide for deciding the most successful sequencing strategy for biocontrol agents. Gene discovery involves quantitative trait loci analyses, transcriptomic and proteomic studies, and gene editing. Improving biocontrol practices includes marker-assisted selection, genomic selection and microbiome manipulation of biocontrol agents, and monitoring for genetic variation during rearing and post-release. We conclude by identifying the most promising applications of genetic and genomic methods to improve biological control efficacy.

What are the costs of learning? Modest trade-offs and constitutive costs do not set the price of fast associative learning ability in a parasitoid wasp

Learning ability has been associated with energetic costs that typically become apparent through trade-offs in a wide range of developmental, physiological, and life-history traits. Costs associated with learning ability can be either constitutive or induced, depending on whether they are always incurred or only when information is actively learned and memorized. Using lines of the parasitoid wasp Nasonia vitripennis that were selected for fast associative learning ability, we assessed a range of traits that have previously been identified as potential costs associated with learning. No difference in longevity, lipid reserves, tibia length, egg load, or fecundity was observed between the selected and control lines. All of these traits are considered to potentially lead to constitutive costs in the setup of this study. A gradual reversal to baseline learning after two forms of relaxed selection was indicative of a small constitutive cost of learning ability. We also tested for a trade-off with other memory types formed at later stages, but found no evidence that the mid-term memory that was selected for caused a decrease in performance of other memory types. In conclusion, we observe only one minor effect of a constitutive cost and none of the other costs and trade-offs that are reported in the literature to be of significant value in this case. We, therefore, argue for better inclusion of ecological and economic costs in studies on costs and benefits of learning ability.

The Jewel Wasp Standard Brain: Average shape atlas and morphology of the female Nasonia vitripennis brain

Nasonia, a genus of parasitoid wasps, is a promising model system in the study of developmental and evolutionary genetics, as well as complex traits such as learning. Of these "jewel wasps", the species Nasonia vitripennis is widely spread and widely studied. To accelerate neuroscientific research in this model species, fundamental knowledge of its nervous system is needed. To this end, we present an average standard brain of recently eclosed naïve female N. vitripennis wasps obtained by the iterative shape averaging method. This "Jewel Wasp Standard Brain" includes the optic lobe (excluding the lamina), the anterior optic tubercle, the antennal lobe, the lateral horn, the mushroom body, the central complex, and the remaining unclassified neuropils in the central brain. Furthermore, we briefly describe these well-defined neuropils and their subregions in the N. vitripennis brain. A volumetric analysis of these neuropils is discussed in the context of brains of other insect species. The Jewel Wasp Standard Brain will provide a framework to integrate and consolidate the results of future neurobiological studies in N. vitripennis. In addition, the volumetric analysis provides a baseline for future work on age- and experience-dependent brain plasticity.